Phase III: Natural Gas-Fired Electric Power Generation Infrastructure Analysis An Analysis of Pipeline Capacity Availability Appendix Gregory L. Peters President, EnVision Energy Solutions [email protected] 804.378.0770 1 Disclaimer: This report was prepared by Gregory L. Peters, President and Principal Consultant of EnVision Energy Solutions, for the benefit of the Midcontinent Independent Transmission System Operator (MISO). This work involves detailed analyses of interstate pipeline daily flow and capacity data; data obtained and compiled by Bentek Energy; and available public information from independent third parties. The appropriate professional diligence has been applied in the preparation of this analysis, using what is believed to be reasonable assumptions. However, since the report also necessarily involves assumptions regarding the future and the accuracy of the data, no warranty is made, expressed or implied. EnVision Energy Solutions is the prime contractor and Bentek Energy is the subcontractor for this analysis. 2 Table of Contents A1 MBA Methodology Details………………………………………………………………………………….6 A1.1 Summary of Pipeline Capacity Availability for Additional Gas-fired Generation....14 A2 Specific Pipeline Overview and Analyses……………………………………………………………18 A2.1 Alliance Pipeline, LP (Segment 1)……..……………………………………………………….…..….18 A2.2 ANR Pipeline Co. (Segments 2, 3, 4) …………..……………………………………………………..21 A2.3 CenterPoint (Enable) MRT (Segment 5)………………………………………………..……………26 A2.4 Great Lakes Transmission (Segment 6)……………………………………………………………….29 A2.5 Guardian Pipeline (Segment 7)...............................................................................31 A2.6 Midwestern Gas Transmission (Segment 8)………….………………………………………..…..33 A2.7 Natural Gas Pipeline Co. of America (Segments 9 and 10)……………………..……….…..37 A2.8 Northern Border Pipeline Company (Segment 11)…………………..…………………….……42 A2.9 Northern Natural Gas Co. (Segment 12)………………….………………………….……………….45 A2.10 Panhandle Eastern Pipe Line Co (Segment 13)……………………………………………….……48 A2.11 Rockies Express Pipeline (Segment 14)……………..…………………………………………….….50 A2.12 Texas Gas Transmission (Segment 15)……………………………………..…………………….……53 A2.13 Trunkline Gas Company (Segment 16)…………………………………………………………….…..57 A2.14 Viking Gas Transmission (Segment 17)……………………………………………………………..…60 A2.15 WBI Energy Transmission (Segment 18)………………………………………..………………..…..62 A2.16 Contributions and Comments by the Natural Gas Industry and EPSA to the Phase I and II Analyses………………………………………………………………………………..……….65 List of Figures Figure A2-1: Alliance System Map Figure A2-2: ANR Outage Map Pipeline Segments Figure A2-3: Power Plants on ANR Figure A2-4: CenterPoint (Enable) MRT System Map Figure A2-5: CenterPoint (Enable) MRT Inflows and Outflows Figure A2-6: CEGT MRT Receipts within MISO Figure A2-7: Great Lakes Gas Transmission System Map Figure A2-8: Guardian Pipeline Map Figure A2-9: Midwestern Pipeline System Map Figure A2-10: Midwestern Multiple Interconnection Flow Options 3 Figure A2-11: Midwestern Northbound and Southbound Flow Customers Figure A2-12: NGPL System System Map Figure A2-13: NGPL System Assets Map Figure A2-14: Northern Border System Capacity Map Figure A2-15: Northern Natural Gas System Map Figure A2-16: Northern Natural Line Constraints Figure A2-17: PEPL System Map Figure A2-18: REX Gas System Map Figure A2-19: Texas Gas Transmission System Map Figure A2-20: Texas Gas Transmission Capacity Flow Patterns Figure A2-21: Trunkline Gas Company System Map Figure A2-22: Trunkline Capacity Flow Patterns Figure A2-23: Viking System Map Figure A2-24: WBI Energy System Map Figure A2-25: Dakota Pipeline System Map List of Tables Table A1.1-1: MWs for CCs and CTs allocated to pipelines and LDCs Table A1.1-2: LDCs with Embedded Units and Requirements Allocation Table A1.1-3: Base Demand Case CC and CT Requirements by Pipeline Table A1.1-4: High Demand Case CC and CT Requirements by Pipeline Table A2-1: Alliance: Base Demand Case Days of Unavailable IT Capacity Table A2-2: Alliance: High Demand Case Days of Unavailable IT Capacity Table A2-3: ANR SE-C: Base Demand Case Days of Unavailable IT Capacity Table A2-4: ANR SE-C: High Demand Case Days of Unavailable IT Capacity Table A2-5: ANR N IL–WI: Base Demand Case Days of Unavailable IT Capacity Table A2-6: ANR N IL–WI: High Demand Case Days of Unavailable IT Capacity Table A2-7: ANR N IL-MI: Base Demand Case Days of Unavailable IT Capacity Table A2-8: ANR N IL-MI: High Demand Case Days of Unavailable IT Capacity Table A2-9: MRT: Base Demand Case Days of Unavailable IT Capacity Table A2-10: MRT: High Demand Case Days of Unavailable IT Capacity Table A2-11: GLGT: Base Demand Case Days of Unavailable IT Capacity Table A2-12: GLGT: High Demand Case Days of Unavailable IT Capacity Table A2-13: Guardian: Base Demand Case Days of Unavailable IT Capacity Table A2-14: Guardian: High Demand Case Days of Unavailable IT Capacity Table A2-15: Midwestern: Base Demand Case Days of Unavailable IT Capacity Table A2-16: Midwestern: High Demand Case Days of Unavailable IT Capacity Table A2-17: NGPL SE: Base Demand Case Days of Unavailable IT Capacity Table A2-18: NGPL SE: High Demand Case Days of Unavailable IT Capacity Table A2-19: NGPL Amarillo: Base Demand Case Days of Unavailable IT Capacity Table A2-20: NGPL Amarillo: High Demand Case Days of Unavailable IT Capacity Table A2-21: Northern Border Base Demand Case Days of Unavailable IT Capacity Table A2-22: Northern Border: High Demand Case Days of Unavailable IT Capacity Table A2-23: Northern Natural Base Demand Case Days of Unavailable IT Capacity 4 Table A2-24: Northern Natural High Demand Case Days of Unavailable IT Capacity Table A2-25: PEPL Base Demand Case Days of Unavailable IT Capacity Table A2-26: PEPL High Demand Case Days of Unavailable IT Capacity Table A2-27: REX Base Demand Case Days of Unavailable IT Capacity Table A2-28: REX High Demand Case Days of Unavailable IT Capacity Table A2-29: TGT Base Demand Case Days of Unavailable IT Capacity Table A2-30: TGT High Demand Case Days of Unavailable IT Capacity Table A2-31: Trunkline Base Demand Case Days of Unavailable IT Capacity Table A2-32: Trunkline High Demand Case Days of Unavailable IT Capacity Table A2-33: Viking Base Demand Case Days of Unavailable IT Capacity Table A2-34: Viking High Demand Case Days of Unavailable IT Capacity Table A2-35: WBI Base Demand Case Days of Unavailable IT Capacity Table A2-36: WBI High Demand Case Days of Unavailable IT Capacity 5 A1 MBA Methodology Details The details of MISO and Bentek methodologies are explained in the main body of the Report. Explained below are the details of how the Modified Backcast Analysis (MBA) allocated MWs for combined cycle units (CCs) and combustion turbine units (CTs) to pipelines and LDCs and how these MWs gas requirements were allocated to the pipelines in the Base and High Demand Case CC and CT gas Cases. The Phase III MBA uses the same methodology as Phase I and II to simulate the impact on pipeline capacity of embedded generation and incremental generation requirements. MISO, through the use of its models, provided the inputs to determine individual unit fuel burns that were applied to historical pipeline flow data. This determines adequacy of natural gas infrastructure to serve projected demand on a pipeline-by-pipeline basis. The MBA is a screening analysis of the pipelines’ main line capacity into their market areas in the MISO region. This is a high-level “screening” analysis or “snapshot” of MISO-region pipelines’ main line capacity based on publically-available data at major interconnections into each pipeline’s market area and is intended to serve as an indicator of capacity availability into the pipelines’ MISO market areas. This Analysis tests the impact of increased natural gas demand on actual historic pipeline flowing volumes and capacity requirements due to a potential 12.6 GW (12K scenario) of coal-to-gas conversions operating at expected and maximum capacity factors. This Analysis is not intended to be a detailed market-area engineering analysis that uses sophisticated flow modeling and other types of transient flow analyses that analyzes each detailed market area pipeline segment’s operational inter- dependencies down to the detailed pipe sizes and pressures at the power plant delivery point levels as it would require access to the pipelines’ proprietary data and information. From a modeling perspective, the Analyses are based on what may be more accurately described as a “Modified-Backcast Scenario Technique” analytical approach based the pipelines’ forward-haul main line capacity using location-specific actual historical flow data into the MISO region. 6 The benefits of the MBA Approach also include: Reveals the number of days in which pipeline capacity would have been insufficient without year-round firm transportation arrangements for the gas pipeline capacity requirements. Identifies seasonal pipeline throughput trends to determine impacts of shifts in macroeconomic variables such as supply location, demands, etc. Establishes a baseline to provide insight to changes in pipeline flow patterns impacted by macroeconomic variables. Provides perspective on the relative strengths of one pipeline to another based on competition, new entrants and sourcing shifts. Reveals how similarly-situated pipelines’ throughput changes due to such factors as changing capacity from competing pipelines. Uses actual nomination flow data from each respective pipeline’s electronic bulletin board or “EBB” data and historical actual maximum flowing capacity data as compiled by Bentek Energy. Application of real-life data and experiences over an extended period 2005 -2013 to evaluate impacts and determine insights to pipelines supply and demand dynamics. This Analysis applied MISO’ s gas delivery requirements for the period 2013-2032 for existing units and the incremental, forecasted gas-fired requirements under 12,000 MW coal-to-gas retirement scenarios. The embedded requirements and the incremental 12,000 MW requirements were converted to Dekatherm gas requirements and applied to historic actual flows and compared to the respective pipeline’s daily maximum flow design capabilities.